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ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 3h

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Interacted two-stage least squares with treatment effect heterogeneity (Zhao, Ding, Li) Treatment effect heterogeneity with respect to covariates is common in instrumental variable (IV) analyses. An intuitive approach, which we term the interacted two-stage least squares (2SLS), is to pos

ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 5h

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Interpreting the Win Ratio in Hierarchical Composite Endpoints: Challenges, Limitations, and Perspectives with Examples from Chronic Kidney Disease Trials (Thomsen, Gasparyan, Furberg et al) Win statistics based methods have gained traction as a method for analyzing Hierarchical Composite

ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 8h

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Outcome-Informed Weighting for Robust ATE Estimation (Yang, Evans) Reliable causal effect estimation from observational data requires adjustment for confounding and sufficient overlap in covariate distributions between treatment groups. However, in high-dimensional settings, lack of overl

ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 11h

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Likelihood-based Inference for Random Networks with Changepoints () Generative, temporal network models play an important role in analyzing the
dependence structure and evolution patterns of complex networks. Due to the
complicated nature of real network data, it is often naive to assume

ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 14h

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Debiased Machine Learning U-statistics (Escanciano, Terschuur) We propose a method to debias estimators based on U-statistics with Machine Learning (ML) first-steps. Standard plug-in estimators often suffer from regularization and model-selection biases, producing invalid inferences. We s

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ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 14h

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A Bernstein polynomial approach for the estimation of cumulative distribution functions in the presence of missing data (Gharbi, Jedidi, Khardani et al) We study nonparametric estimation of univariate cumulative distribution functions (CDFs) pertaining to data missing at random. The propo

ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 14h

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Root Cause Analysis of Outliers in Unknown Cyclic Graphs (Schkoda, Janzing) We study the propagation of outliers in cyclic causal graphs with linear structural equations, tracing them back to one or several "root cause" nodes. We show that it is possible to identify a short list of potent

ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 14h

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Nonparametric Estimation of Self- and Cross-Impact (Hey, Neuman, Tuschmann) We introduce an offline nonparametric estimator for concave multi-asset propagator models based on a dataset of correlated price trajectories and metaorders. Compared to parametric models, our framework avoids par

ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 14h

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Testing the equality of estimable parameters across many populations (Romero-Madro\~nal, Sillero-Denamiel, Jim\'enez-Gamero) The comparison of a parameter in $k$ populations is a classical problem in statistics. Testing for the equality of means or variances are typical examples. Most pro

ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 14h

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Estimating temporary emigration from capture-recapture data in the presence of latent identification (Skopalova, Osuna, Zhang) Most capture-recapture models assume that individuals either do not emigrate or emigrate permanently from the sampling area during the sampling period. This assum

ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 14h

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Incorporating Expert Knowledge into Bayesian Causal Discovery of Mixtures of Directed Acyclic Graphs (Bj\"orkman, Lor\'ia, Wharrie et al) Bayesian causal discovery benefits from prior information elicited from domain experts, and in heterogeneous domains any prior knowledge would be badly

ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 14h

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A Mixed-Methods Analysis of Repression and Mobilization in Bangladesh's July Revolution Using Machine Learning and Statistical Modeling (Siddiqui, Roy) The 2024 July Revolution in Bangladesh represents a landmark event in the study of civil resistance. This study investigates the central

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ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 14h

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Beyond the Oracle Property: Adaptive LASSO in Cointegrating Regressions (Reichold, Schneider) This paper establishes new asymptotic results for the adaptive LASSO estimator in cointegrating regression models. We study model selection probabilities, estimator consistency, and limiting dist

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ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 14h

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Bayesian Portfolio Optimization by Predictive Synthesis (Kato, Baba, Kaibuchi et al) Portfolio optimization is a critical task in investment. Most existing portfolio optimization methods require information on the distribution of returns of the assets that make up the portfolio. However,

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ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 14h

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Randomization Restrictions: Their Impact on Type I Error When Experimenting with Finite Populations (Chipman, Sverdlov, Uschner) Participants in clinical trials are often viewed as a unique, finite population. Yet, statistical analyses often assume that participants were randomly sampled

ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 14h

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jmstate, a Flexible Python Package for Multi-State Joint Modeling (Laplante, Ambroise, Kuhn et al) Classical joint modeling approaches often rely on competing risks or recurrent event formulations to account for complex real-world processes involving evolving longitudinal markers and disc

ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 14h

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On Assessing Overall Survival (OS) in Oncology Studies (Hsu) In assessing Overall Survival (OS) in oncology studies, it is essential for the efficacy measure to be Logic-respecting, for otherwise patients may be incorrectly targeted. This paper explains, while Time Ratio (TR) is Logic-res

ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 14h

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Confidence Regions for Multiple Outcomes, Effect Modifiers, and Other Multiple Comparisons (Zivich, Cole, Greifer et al) In epidemiology, some have argued that multiple comparison corrections are not necessary as there is rarely interest in the universal null hypothesis. From a parameter

ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 14h

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Inference in pseudo-observation-based regression using (biased) covariance estimation and naive bootstrapping (Mack, Overgaard, Dobler) We demonstrate that the usual Huber-White estimator is not consistent for the limiting covariance of parameter estimates in pseudo-observation regression

ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 14h

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Rank Aggregation under Weak Stochastic Transitivity via a Maximum Score Estimator (Zhang, Chen) Stochastic transitivity is central for rank aggregation based on pairwise comparison data. The existing models, including the Thurstone, Bradley-Terry (BT), and nonparametric BT models, adopt a

ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 14h

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Likelihood-based inference for the Gompertz model with Poisson errors (Onorati, Ruiz-Suarez, Craiu) Population dynamics models play an important role in a number of fields, such as actuarial science, demography, and ecology. Statistical inference for these models can be difficult when, in

ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 14h

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Maximum softly penalised likelihood in factor analysis (Sterzinger, Kosmids, Moustaki) Estimation in exploratory factor analysis often yields estimates on the boundary of the parameter space. Such occurrences, known as Heywood cases, are characterised by non-positive variance estimates an

ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 1d

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A Supervised Machine Learning Approach for Assessing Grant Peer Review Reports () arXiv:2411.16662v1 Announce Type: new
Abstract: Peer review in grant evaluation informs funding decisions, but the contents of peer review reports are rarely analyzed. In this work, we develop a thoroughly

ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 1d

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Universally Optimal Multivariate Crossover Designs () In this article, universally optimal multivariate crossover designs are
studied. The multiple response crossover design is motivated by a $3 \times 3$
crossover setup, where the effect of $3$ doses of an oral drug are studied on
gene e

ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 1d

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An utopic adventure in the modelling of conditional univariate and multivariate extremes () The EVA 2023 data competition consisted of four challenges, ranging from
interval estimation for very high quantiles of univariate extremes conditional
on covariates, point estimation of unconditio